121 lines
4.2 KiB
Markdown
121 lines
4.2 KiB
Markdown
# Kohya's dreambooth and finetuning
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This repository now includes the solutions provided by Kohya_ss in a single location. I have combined both solutions under one repository to align with the new official Kohya repository where he will maintain his code from now on: https://github.com/kohya-ss/sd-scripts.
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A note accompanying the release of his new repository can be found here: https://note.com/kohya_ss/n/nba4eceaa4594
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## Installation
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Open a regular Powershell terminal and type the following inside:
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```powershell
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git clone https://github.com/bmaltais/kohya_ss.git
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cd kohya_ss
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python -m venv --system-site-packages venv
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.\venv\Scripts\activate
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pip install torch==1.12.1+cu116 torchvision==0.13.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116
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pip install --upgrade -r requirements.txt
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pip install -U -I --no-deps https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/f/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl
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cp .\bitsandbytes_windows\*.dll .\venv\Lib\site-packages\bitsandbytes\
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cp .\bitsandbytes_windows\cextension.py .\venv\Lib\site-packages\bitsandbytes\cextension.py
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cp .\bitsandbytes_windows\main.py .\venv\Lib\site-packages\bitsandbytes\cuda_setup\main.py
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accelerate config
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```
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### Optional: CUDNN 8.6
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This step is optional but can improve the learning speed for NVidia 4090 owners...
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Due to the filesize I can't host the DLLs needed for CUDNN 8.6 on Github, I strongly advise you download them for a speed boost in sample generation (almost 50% on 4090) you can download them from here: https://b1.thefileditch.ch/mwxKTEtelILoIbMbruuM.zip
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To install simply unzip the directory and place the cudnn_windows folder in the root of the kohya_diffusers_fine_tuning repo.
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Run the following command to install:
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```
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python .\tools\cudann_1.8_install.py
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```
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## Upgrade
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When a new release comes out you can upgrade your repo with the following command:
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```powershell
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cd kohya_ss
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git pull
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.\venv\Scripts\activate
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pip install --upgrade -r requirements.txt
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```
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Once the commands have completed successfully you should be ready to use the new version.
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## Launching the GUI
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To run the GUI you simply use this command:
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```
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gui.cmd
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```
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## Dreambooth
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You can find the dreambooth solution spercific [Dreambooth README](README_dreambooth.md)
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## Finetune
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You can find the finetune solution spercific [Finetune README](README_finetune.md)
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## LoRA
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You can create LoRA network by running the dedicated GUI with:
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```
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python lora_gui.py
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```
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or via the all in one GUI:
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```
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python kahya_gui.py
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```
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Once you have created the LoRA network you can generate images via auto1111 by installing the extension found here: https://github.com/kohya-ss/sd-webui-additional-networks
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## Change history
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* 2023/01/06 (v19.4):
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- Add new Utility to Extract a LoRA from a finetuned model
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* 2023/01/06 (v19.3.1):
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- Emergency fix for dreambooth_ui no longer working, sorry
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- Add LoRA network merge too GUI. Run `pip install -U -r requirements.txt` after pulling this new release.
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* 2023/01/05 (v19.3):
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- Add support for `--clip_skip` option
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- Add missing `detect_face_rotate.py` to tools folder
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- Add `gui.cmd` for easy start of GUI
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* 2023/01/02 (v19.2) update:
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- Finetune, add xformers, 8bit adam, min bucket, max bucket, batch size and flip augmentation support for dataset preparation
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- Finetune, add "Dataset preparation" tab to group task specific options
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* 2023/01/01 (v19.2) update:
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- add support for color and flip augmentation to "Dreambooth LoRA"
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* 2023/01/01 (v19.1) update:
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- merge kohys_ss upstream code updates
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- rework Dreambooth LoRA GUI
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- fix bug where LoRA network weights were not loaded to properly resume training
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* 2022/12/30 (v19) update:
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- support for LoRA network training in kohya_gui.py.
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* 2022/12/23 (v18.8) update:
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- Fix for conversion tool issue when the source was an sd1.x diffuser model
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- Other minor code and GUI fix
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* 2022/12/22 (v18.7) update:
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- Merge dreambooth and finetune is a common GUI
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- General bug fixes and code improvements
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* 2022/12/21 (v18.6.1) update:
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- fix issue with dataset balancing when the number of detected images in the folder is 0
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* 2022/12/21 (v18.6) update:
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- add optional GUI authentication support via: `python fine_tune.py --username=<name> --password=<password>` |